QNM222 - Business Statistics

Outline information
Schools offering this subject
Last revision date May 25, 2020 12:07:38 AM
Last review date Jul 13, 2020 12:15:02 AM

Subject Title
Business Statistics

Subject Description
The statistical methods of collection, analysis, presentation and interpretation of quantitative data used for making generalizations, projections and decisions under uncertain conditions are introduced. Emphasis will be on the use of both descriptive and inferential statistical techniques within the workplace. Students may utilize spreadsheet software to present and analyse data.

Credit Status
QNM 222 is a one credit subject.

Learning Outcomes
Upon successful completion of this subject the student will be able to:

1. Demonstrate the ability to present, describe, and summarize data by:

  • identifying the different types of data
  • differentiating between a population and a sample
  • re-organizing raw data into arrays and grouped distributions
  • presenting data by means of various tables and graphing methods using computer software/manual techniques
  • calculating various measures of location and dispersion, including the mean, median, mode, percentiles, quartiles, standard deviation, and variance Spreadsheet software may be used to assist in these calculations
  • describing the shape of a distribution
  • comparing and evaluating alternative methods of presenting data.

2. Evaluate with the use of probability, the likelihood that a statistical inference is correct by:
  • defining probability
  • differentiating between subjective, relative frequency and classical approaches
  • determining when events are mutually exclusive and/or statistically independent
  • calculating probabilities using the rules of addition and multiplication

3. Determine the characteristics of selected probability distributions and identify where each distribution can be applied by:
  • differentiating between discrete and continuous random variables
  • determining the probability of events and calculating the means (expected value) and standard deviations of:
    • the probability distribution of a discrete random variable
    • the binomial probability distribution

4. Recognize normal distribution problems and know how to solve such problems by:
  • calculating the z-value corresponding to any observation on a normal distribution
  • determining the probability a random observation is in a given interval on a normal distribution
  • using the normal distribution to approximate the binomial distribution

5. Use the central limit theorem to:
  • calculate the mean and standard error of a random variable
  • calculate probabilities for a given sample mean

6. Use sample data to make statements about the value of the population mean or proportion by:
  • differentiating between a point estimator and an interval estimator
  • calculating the point estimate for the population mean or proportion
  • determining the confidence intervals for the population mean using sample mean and population standard deviation for large or small sized samples
  • determining the confidence interval for population proportion for large or small sized samples
  • computing the required sample size to estimate the population mean and population proportion for large or small sized samples

7. Construct and evaluate hypothesis test of a mean or proportion by:
  • stating the null hypothesis and the alternative hypothesis
  • indicating the appropriate test statistic
  • establishing the critical value(s) of the test statistic
  • calculating the actual value of the test statistic and drawing appropriate conclusions

8. Perform simple regression and correlation analysis in business situations as indicated by:
  • interpreting a scatter diagram
  • determining and interpreting the correlation coefficient and the coefficient of determination
  • differentiating between a dependent variable and an independent variable
  • determining and interpreting the coefficients of the sample regression line
  • using a regression equation to predict the value of the dependent variable for a selected value of the independent variable
  • conduct a test of hypothesis for the coefficent of correlation and each coefficent of regression
  • using spreadsheet software to perform the regression analysis
  • interpret confidence intervals and prediction intervals for the dependent variable

Essential Employability Skills
Execute mathematical operations accurately.

Apply a systematic approach to solve problems.

Use a variety of thinking skills to anticipate and solve problems.

Take responsibility for one's own actions, decisions, and consequences.

Academic Integrity
Seneca upholds a learning community that values academic integrity, honesty, fairness, trust, respect, responsibility and courage. These values enhance Seneca's commitment to deliver high-quality education and teaching excellence, while supporting a positive learning environment. Ensure that you are aware of Seneca's Academic Integrity Policy which can be found at: http://www.senecacollege.ca/about/policies/academic-integrity-policy.html Review section 2 of the policy for details regarding approaches to supporting integrity. Section 2.3 and Appendix B of the policy describe various sanctions that can be applied, if there is suspected academic misconduct (e.g., contract cheating, cheating, falsification, impersonation or plagiarism).

Please visit the Academic Integrity website http://open2.senecac.on.ca/sites/academic-integrity/for-students to understand and learn more about how to prepare and submit work so that it supports academic integrity, and to avoid academic misconduct.

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Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Accessibility Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.